Model/Anlys/Valid Analyst II - C10 - MUMBAI

About Citi

The Model Risk Management (MRM) organization provides oversight for the Model Risk Management Framework, which consists of the policy, processes, and procedures through which Citi identifies, measures, manages, monitors, reports, and controls model risk across the firm. This position is a unique opportunity to learn how the trading book models are developed and validated in a Tier one Global Investment Bank.

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Description

Model Risk Management (MRM) is an independent oversight function. The Mumbai center is one of the major MRM locations across the globe and is responsible for development and maintenance of Model Risk Management Policy and procedures, for evaluation and approval of models used across the firm.

There is a significant increase in the scope and depth of model validation activities across the firm to meet the commitments made to the regulators and to meet the Model Risk Management Policy standards for the firm.

We are looking for Model Risk validators to conduct the validation for models spanning the International Banking and Markets space including quantitative Risk models, wholesale credit risk models, market risk models and Algorithmic Trading models. This is an exciting role in Mumbai in a growing a team of validators for ICG models. The scope of model validation will be varied and can span any of the following areas:

• Quantitative Risk models, such as Wholesale Credit Risk, Market risk, Liquidity Risk, etc. which are used to assess the adequacy of risk capital and estimated losses for regulatory or business requirements (including CCAR/DFAST, CECL, IFRS9, ICAAP, Basel, Financial Planning, Internal Stress Testing, etc.).
• Market Risk with focus areas including Market Risk (e.g. Fundamental Review of Trading Book), Comprehensive Capital Analysis and Review (CCAR), Internal Capital Adequacy Assessment Process (ICAAP), Economic Risk Capital, etc.

There will be plenty of learning and growth opportunities with this position, from both technical and leadership perspective. The incumbent will be exposed to different areas of business activities and a variety of modeling approaches, including machine learning and industry standard tools.

The validation covers both technical and functional aspects, including model assumptions, conceptual soundness, mathematical formulation, model calibration, and model performance, as well as the functional assessment of using the model for regulatory and business applications. Job responsibilities include reviewing models and identifying shortcomings development documents, performing validation tests, discussing findings with senior stakeholders, writing validation reports, and managing model risk on an ongoing basis.

Key Responsibilities:

• Support the review and validation of models as per MRM framework, provide effective challenge, ensuring validation work quality.
• Help manage model risk across the model lifecycle including model validation, performance evaluation and annual model reviews.
• Work with lead validators on critical projects like revalidations.
• Independently delivering on monitoring projects like OPAs and AMRs.

Qualifications

Required:

• Minimum of Master’s degree in a quantitative field (Statistics, Mathematics, Physics, Engineering, Computer science, etc.)
• Higher academic qualifications, a second Master’s degree, FRM, CPA or CFA is a plus
• Must have a strong background in statistical modelling techniques.
• Good understanding of Model Risk Management and framework like SR 11-7.
• Programming skills in using one or more of programming languages, such as Python, SAS, SQL, R, etc.
• Proficient in Microsoft Office (Word, Excel, and PowerPoint)
• 0-2 years’ experience in model implementation/validation/development is compulsory.
• Strong written and oral communication skills.
• Teamwork and commitment a must as well ability to work independently.

Preferable:

• Knowledge and understanding of a variety of model development and validation testing techniques covering risk models, including but not limited to linear regression models, logistic regression, generalized additive models, decision and regression trees, information gain and related segmentation statistical tools. Previous familiarity with Risk models such as Credit Risk, Market Risk, Liquidity Risk, Scenario Variables/ Macroeconomic Forecasting models etc. is preferred.
• Knowledge of financial instruments, simulation and risk estimation methodologies, and regulatory requirements.

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Job Family Group:

Risk Management

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Job Family:

Risk Analytics, Modeling, and Validation

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Time Type:

Full time

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